This is the title of an article in the Jul-13 issue of the Wired Magazine UK Edition. It refers to the rendering of the first 100 billion digits of pi proving that they're random at CARMA.
The makers used a random walk software that drew the image and colored the points from the beginning (red) to the 100 billion digits (violet). And yes, it looks random - no patterns recognizable.
I remember when I was a maths student the first example of "undecidability": how many "123" sequences will you find in the decimal fraction of pi?
However, a great idea .. but "reinvent maths"? Why so black and white?
This reminds me that I had an exciting discussion with another Wilmott member in the "General Forum" about the question: what can we learn from past economic models ... recently?
We agreed: not much, because we need to understand that complexity economics if different from the classical (equilibrium) economic approaches.
"we have now more data but less knowledge", he summarized the difficulties ... "less computational knowledge", I add. We need new nonlinear models ..... That is another challenge for maths?
Helping us to understand that it is difficult to calculate "expected" returns in finance by just looking into ensemble averages and not time ... as described here.
Graphs and images will help us a lot, but we shall not forget to improve models, understand why they need accurate and robust solvers and need to be calibrated and re-calibrated constantly.
